Which of count (*), count (primary key ID), count (field) and count (1) in MySQL is more efficient? "Suggested collection"

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stay select count(?) from t In such query statements ,count(*)、count( Primary key id)、count( Field ) and count(1) And so on , What are the differences .

It should be noted that , The following discussion is based on InnoDB Engine .

here , First of all, you have to find out count() The semantics of the .count() It's an aggregate function , For the returned result set , Judge line by line , If count The argument to the function is not NULL, Add... To the cumulative value 1, Otherwise, we will not add . Finally return the cumulative value .

therefore ,count(*)、count( Primary key id) and count(1) All indicates that the total number of result sets satisfying the conditions is returned ; and count( Field ）, It means to return the data line that meets the conditions , Parameters “ Field ” Not for NULL Total number of .

When it comes to analyzing performance differences , You can remember these principles ：

1. server Give the floor whatever you want ;
2. InnoDB Give only the necessary value ;
3. Now the optimizer only optimizes count(*) The meaning of is “ Take the number of lines ”, other “ Obvious ” The optimization of is not done .

What does that mean ？ Next , Let's take a look one by one .

about count( Primary key id) Come on ,InnoDB The engine will traverse the entire table , Put each line of id Take out all the values , Return to server layer .server Get the floor id after , Judgment cannot be empty , Just add up by lines .

about count(1) Come on ,InnoDB The engine traverses the entire table , But no value .server Layer for each row returned , Put a number “1” go in , Judgment cannot be empty , Add by line .

Just look at the difference between these two usages , You can compare ,count(1) Perform better than count( Primary key id) fast . Because back from the engine id It's going to involve parsing the data lines , And copy field values .

about count( Field ) Come on ：

1. If this “ Field ” Is defined as not null Words , Read the field line by line from the record , Judgment cannot be null, Add by line ;
2. If this “ Field ” The definition is allowed to be null, So when it comes to execution , To judge that it might be null, We need to take out the value and judge again , No null Just add up .

That's the first principle ,server What fields does the layer want ,InnoDB What fields are returned .

however count(*) It's an exception , It doesn't take all the fields out , It's optimized , No value .count(*) Definitely not null, Add by line .

See here , You must say , Can't the optimizer judge for itself , Primary key id It must be empty , Why can't we follow count(*) To deal with it , What a simple optimization .

Of course ,MySQL Optimized specifically for this statement , It's not impossible . But there are too many situations that require specialized optimization , and MySQL Has been optimized count(*) 了 , You can just use this usage directly .

So the conclusion is ：

In order of efficiency ,count( Field )<count( Primary key id)<count(1)≈count(*), So I suggest you , Use as much as possible count(*).

We mentioned that in different engines count(*) The implementation of is different , The problems of using cache system to store count values are also analyzed .

Actually , Put the count on Redis Inside , Counting and... Cannot be guaranteed MySQL The reason why the data in the table are accurate and consistent , yes These two different storage systems , Distributed transactions are not supported , Can't get an accurate and consistent view . And put the count value in MySQL in , This solves the problem of consistent view .

InnoDB Engine support transactions , We make good use of the atomicity and isolation of transactions , You can simplify the logic in business development . This is also InnoDB One of the reasons why engines are popular .

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